Armstrong Samuel E, Klusty Mitchell A, Mullen Aaron D, Talbert Jeffery C, Bumgardner Cody
Institute for Biomedical Informatics, University of Kentucky, Lexington, KY.
AMIA Jt Summits Transl Sci Proc. 2025 Jun 10;2025:56-64. eCollection 2025.
Developing and enforcing study protocols is crucial in medical research, especially as interactions with participants become more intricate. Traditional rules-based systems struggle to provide the automation and flexibility required for real-time, personalized data collection. We introduce SmartState, a state-based system designed to act as a personal agent for each participant, continuously managing and tracking their unique interactions. Unlike traditional reporting systems, SmartState enables real-time, automated data collection with minimal oversight. By integrating large language models to distill conversations into structured data, SmartState reduces errors and safeguards data integrity through built-in protocol and participant auditing. We demonstrate its utility in research trials involving time-dependent participant interactions, addressing the increasing need for reliable automation in complex clinical studies.
制定和执行研究方案在医学研究中至关重要,尤其是随着与参与者的互动变得更加复杂。传统的基于规则的系统难以提供实时、个性化数据收集所需的自动化和灵活性。我们引入了SmartState,这是一个基于状态的系统,旨在作为每个参与者的个人代理,持续管理和跟踪他们独特的互动。与传统报告系统不同,SmartState能够以最少的监督实现实时、自动数据收集。通过集成大语言模型将对话提炼为结构化数据,SmartState减少错误并通过内置协议和参与者审核保障数据完整性。我们展示了它在涉及时间依赖性参与者互动的研究试验中的效用,满足了复杂临床研究对可靠自动化日益增长的需求。